Enhancing the predictive power of population dynamics models for highly migratory fish species with the use of data from advanced survey technologies

本研究旨在利用先进的调查技术数据，提高高洄游鱼类种群动态模型的准确性和预测能力。目标包括：(1)根据从电子数据存储、无线电遥测和传统标签获得的数据，以及种群识别（ID）研究，即鱼身体部位的遗传和微观成分（MC）分析获得的数据，制定和匹配区域结构和季节结构的种群动态模型。(2)与更常用的数据（如渔业依赖数据和传统标记数据）拟合的模型相比，评估拟合这些数据的模型所获得的丰度估计偏差的潜在减少。(3)设计模型，以评估备选管理行动对所研究鱼类种群的潜在生物学后果。(4)评估一种假设，即在太平洋和地中海蓝鳍金枪鱼种群的几个世纪的开发事件导致这些种群的遗传适应性较低，即成熟年龄为4岁，而南大洋和墨西哥湾种群的成熟年龄为12岁。将为大西洋和太平洋蓝鳍金枪鱼开发新的种群评估模型，该模型将与传统、弹出式和档案标记研究的记录以及其中一些鱼类的遗传种群id相匹配。统计方法重建季节性和个体白鲟的洄游还有待发展。迁移路径模型将适用于100条Nechako河鲟鱼的标记-再捕获，无线电遥测，鳍射线MC数据。将多元统计方法应用于重建的迁徙历史，以识别不同的产卵种群。这些结果将用作空间和种群结构种群动态模型的输入，这些模型将与现有的标记-再捕获数据相拟合，以估计一个或多个产卵种群的年总存活率和丰度。该研究有助于提高对鱼类洄游行为、种群结构和动态、种群动态模型预测的可靠性以及恢复活动的设计的认识，并为应用于其他种群提供了方法。

This study aims to enhance the accuracy and predictive power of population dynamics models for highly migratory fishes with the use of advanced survey technology data. The objectives include: (1) Formulate and fit area-, and seasonally-structured population dynamics models to data obtained from electronic data storage, radio-telemetry and conventional tags, and stock identification (ID) studies, i.e., genetic and micro-constituent (MC) analyses of fish body parts. (2) Evaluate the potential reductions in bias in abundance estimates obtained from models fitted to these data compared to models fitted to more commonly used data such as fisheries dependent data and conventional tagging data only. (3) Project the models to evaluate the potential biological consequences of alternative management actions for the fish populations studied. (4) Evaluate the hypothesis that multi-century episodes of exploitation in the Pacific and Mediterranean populations of bluefin tuna have caused genetic adaptations for lower, i.e., 4 yr age at maturity in these populations compared to that of 12 yrs in the Southern Ocean and Gulf of Mexico populations. New stock assessment models are to be developed for Atlantic and Pacific bluefin tuna that are fitted to records from conventional, pop-up and archival tagging studies and genetic stock IDs from some of these fish. Statistical methods to reconstruct seasonal and ontogenetic migrations of individual white sturgeon are to be developed. Migration pathway models will be fitted to mark-recapture, radio-telemetry, fin ray MC data for 100 Nechako River sturgeon. Multivariate statistical methods will be applied to the reconstructed migration histories to identify different spawning populations. These results will be utilized as inputs to spatially and stock structured population dynamics models that are to be fitted to available mark-recapture data to estimate total annual survival rates and abundance of the one or more spawning stocks. The research offers to improve understanding of fish migratory behaviours, population structure and dynamics, the reliability of predictions from population dynamics models, and the design of recovery activities, and offers methodologies for application to other populations.